code: def get_parsed_conll_output(conll_output_filepath):
      conll_output = [
          l.rstrip()
          .replace("%", "")
          .replace(";", "")
          .replace(":", "")
          .strip()
          for l in codecs.open(conll_output_filepath, "r", "utf8")
      ]
      parsed_output = {}
      line = conll_output[1].split()
      parsed_output["all"] = {
          "accuracy": float(line[1]),
          "precision": float(line[3]),
          "recall": float(line[5]),
          "f1": float(line[7]),
      }
      total_support = 0
      for line in conll_output[2:]:
          line = line.split()
          phi_type = line[0].replace("_", "-")
          support = int(line[7])
          total_support += support
          parsed_output[phi_type] = {
              "precision": float(line[2]),
              "recall": float(line[4]),
              "f1": float(line[6]),
              "support": support,
          }
      parsed_output["all"]["support"] = total_support
      return parsed_output
  
file_path: NeuroNER/neuroner/utils_nlp.py
imports: import codecs
  import os
  import re
  import numpy
  from neuroner import utils
label_desc: Use image node_id 4 for calling a global function with example usage: get_parsed_conll_output(conll_output_filepath) and returns: parsed_output